Urban Visual Intelligence: Studying Cities with Artificial Intelligence and Street-Level Imagery-Reference-Cited by-同舟云学术

Urban Visual Intelligence: Studying Cities with Artificial Intelligence and Street-Level Imagery

Published:2024-04-08 Issue:5 Volume:114 Page:876-897
ISSN:2469-4452
Container-title:Annals of the American Association of Geographers
language:en
Short-container-title:Annals of the American Association of Geographers

Author:

Zhang Fan¹^ORCID,Salazar-Miranda Arianna²³^ORCID,Duarte Fábio²^ORCID,Vale Lawrence³,Hack Gary³,Chen Min⁴^ORCID,Liu Yu¹^ORCID,Batty Michael⁵^ORCID,Ratti Carlo²³

Affiliation:

1. Institute of Remote Sensing and Geographical Information System, School of Earth and Space Sciences, Peking University, China

2. Senseable City Lab, Massachusetts Institute of Technology, USA

3. Department of Urban Studies and Planning, Massachusetts Institute of Technology, USA

4. Key Laboratory of Virtual Geographic Environment, Ministry of Education, Nanjing Normal University, China

5. Centre for Advanced Spatial Analysis, Faculty of the Built Environment, University College London, UK

Funder

National Natural Science Foundation of China

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/24694452.2024.2313515

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5. Defining Urban Science

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